"Memory" matching MCP servers:

Smart memory for AI agents. Solves the Karpathy problem: memories decay, topics are frequency-weighted, one-time questions don't become obsessions. 7 tools. Zero deps.

Provides persistent memory for AI assistants via MCP, enabling them to store and recall facts, preferences, and tasks across conversations using either local file storage or a cloud backend with semantic search.

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

Cognitive memory engine for AI agents with 5,100+ knowledge modules, circadian rhythm awareness, emotional state tracking (PAD model), and hybrid semantic search. Supports persistent per-user memory, project-scoped contexts, and multi-protocol access.

Provides AI agents with associative long-term memory using Sparse Distributed Memory, enabling recall from vague cues and interference detection.

A fully local persistent memory layer for LLM coding agents (Claude Code, Codex, Gemini CLI, OpenCode). A shell wrapper intercepts tool invocations, fires hooks on every tool call, then runs a 3-layer pipeline (extract → compress to ≤500-token digest → merge into project memory doc) at session end. The next session gets prior context injected automatically.

Persistent project memory for AI models and coding agents. Memory MCP stores architecture, decisions, tasks, warnings, preferences, and session state in Supabase so OpenCode, Claude Code CLI, Qwen Code, Codex, or any MCP-compatible client can resume work without losing context.

Provides AI coding agents with a local knowledge-graph memory, enabling cross-project retrieval via PageRank diffusion and tools to retrieve, write, extract, update, and view recent knowledge over MCP.

Persistent cognitive memory for AI agents. Sub-millisecond recall, fully offline, encrypted. 8 tools: recall, recall_structured, store, store_code, store_decision, search, insights, consolidate.

A lightweight MCP server that gives Claude Code Channels on Telegram persistent memory by storing facts, conversation logs, and session summaries in Supabase.

An MCP server that gives AI agents persistent, forgetting memory with layered decay, semantic search via token overlap, and zero external dependencies.

Flux Memory is an MCP server that provides a self-organizing weighted graph memory for AI agents, enabling persistent knowledge storage, retrieval, and feedback-based learning.

Provides MCP tools for persistent, cross-session memory via Cloudflare Agent Memory, enabling agents to store, recall, ingest, summarize, and manage memory namespaces.

Provides AI companion agents a local-first, append-first long-term memory backend with layered memory, hybrid recall, review-based updates, and a continuity sub-brain, exposed via REST and MCP interfaces.

A persistent, conflict-aware memory MCP server for AI coding assistants (Cursor, Claude Code).

Provides brain-inspired long-term memory for MCP clients, enabling persistent user understanding across sessions with Chinese-optimized hybrid retrieval and evolving user profiles.

A vendor-agnostic cognitive persistence layer for AI agents. Eliminate the "repetition tax" by transporting your context, preferences, and history across sessions. Features an auto-adaptation engine that syncs global instructions to ensure operational cohesion and optimize token usage across any LLM or multi-agent workflow.

Local-first agent memory & knowledge service (v2.4.4): hybrid retrieval (vector + BM25) + offline CSV/Excel row-level Q&A without LLM; REST + MCP dual protocol (13 tools incl. list/delete documents); memory governance; Python.

Enables AI assistants across Claude Code, Claude Desktop, Codex CLI, and Gemini CLI to remember and automatically apply user-confirmed behavioral instruction presets, with a trust curve for scheduled re-confirmation and one-command uninstall.

Enables MCP clients like Cursor and Claude to remember user preferences and behaviors across conversations using vector search technology.

Enables LLM clients to store and retrieve per-user long-term memories in SQLite, with tools to add, search, list, get, and delete memories via MCP HTTP/SSE transports.

An advanced cognitive memory agent for AI chatbots that provides long-term, autonomous memory using a four-agent system for monitoring, extraction, reconciliation, and consolidation.

Enables LLM agents to use associative memory with key/value graph-based retrieval, supporting multi-hop traversal and human-like associative leaps beyond embedding similarity.

A Model Context Protocol server providing durable, cross-session memory for AI agents, powered by Qwen on Alibaba Cloud. Enables agents to write, search, recall, and forget memories with semantic ranking.

Enables AI agents to maintain a three-layer memory that decays, consolidates offline through dreaming, and revises impressions, with tools for observing, recalling, tracing, pinning, compacting, and exporting diary entries.

Enables AI agents with persistent semantic memory, including semantic recall, knowledge graphs, and instant domain expertise via pre-built Intelligence Packs.

Enables MCP clients to lint stored agent facts for duplicates, contradictions, and staleness (including implicit conflicts found via local embeddings), and to gate a new fact for admission before it is persisted. It runs read-only over stdio, never writing to a store or calling the network.

Persistent memory MCP server for AI agents, using SQLite with hybrid keyword and semantic search for long-term memory storage.

Enables AI agents to store, semantically recall, update, forget, consolidate, and verify persistent memories with session isolation and hyperbolic concept navigation. It also supports knowledge-graph linking and claim verification for anti-hallucination workflows.

An MCP server that gives AI assistants persistent memory using an OpenAI vector store, enabling saving and semantic searching of text memories across sessions.